Introduction
The issue of quality of life (QOL) has received increased attention
from the medical community due to its importance for patient
rehabilitation (Lustig & Crowder, 2000). QOL is known to be
indicative of the level of social functioning in mental health patients
(Menlowics & Stein, 2000). In an era of
deinstitutionalization, the proliferation of community support programs
has played a pivotal role in providing basic support structures to
patients with mental illness (Jinnett et al., 2001).
However, the maximum level of QOL attainable to patients with chronic
mental illness is a topic for continued discussion.
QOL can be defined as an overall sense of well-being, comprised of both
objective and subjective evaluations of physical, material, social and
emotional well-being together with personal development and purposeful
activity (Felce & Perry, 1996). Measurement of QOL can be a
comprehensive means of evaluating various aspects of care through the
exploration of subjective judgments of persons with severe mental
illness (SMI) of their own welfare and by objective assessments of
their life circumstances by researchers (Clarkson & McCrone,
2000). The subjective QOL refers to the level of satisfaction of
a person with his or her living situation and general well-being, while
objective pertains to how well the patient functions in social settings
and in daily activities (Mares, Young, McGuire, & Rosenheck, 2002).
The level of satisfaction with interpersonal relationships and
subjective QOL of patients with SMI may be lower than for people from
the general population (Tempier, Caron, Mercier & Leouffre, 1998).
QOL derives in large part from social contact (Bigelow et al., 1991).
Social contact fulfills the personal needs of mentally ill individuals
for affection and promotes self-esteem. Social contact also
contributes to a sense of affiliation in people with mental illness
(Corrigan, 2003). Patients with SMI who have access to community
support services report having acceptable levels of satisfaction with
their lives (Trauer et al., 1998). Unfortunately, many activities
that can potentially fulfill basic personal needs for social contact
are unavailable to people with mental illness in mental health
settings. Also, people with mental illness tend to have small,
low-density social networks comprised mainly of family members (Brunt
& Hansson, 2002). This lack of social networks in
mentally ill patients may contribute to the onset of psychopathological
symptoms, which can in turn place a burden on psychiatric services and
in-patient services.
Previous research has demonstrated that heightened social support can
improve the QOL of persons with mental illness (see for example, Yanos
et al., 2001; Nelson et al., 1995). Social support acts to buffer
the impact of stressful experiences, such as those related to physical
health (Swindells et al., 1999). Social support can also moderate
the effects of pain, certain functional limitations, and depression
(Blixen & Kippes, 1999).
It has previously been shown that the quantity of supportive social
relationships is predictive of subjective QOL in persons diagnosed with
severe mental illness (Baker et al. 1992; Bengtsson-Tops & Hannson,
2001; Caon et al. 1998; Hannson et al., 2002; Lam & Rosencheck
2000; Rudnick & Kravetz, 2001). Especially when present within a
context of large network size (Goldberg et al., 2003), social support
can promote recovery in people with serious mental illness (Corrigan
and Phelan, 2004). Mares, Young, McGuire & Rosenheck (2002) found
that a desirable social climate was positively associated with
subjective QOL in mental health patients. Previous researchers have
used the Bigelow Quality of Life Questionnaire (Bigelow et al, 1991) to
individually measure various components of QOL in mental health
patients (Baker et al., 1992; Caron et al., 1998; Goldberg et al.,
2003; Mares et al., 2002; Nelson et al., 1995; Skinner et al., 1999 and
Yanos et al., 2001). Our study was unique in that we assessed all
domains of the Bigelow questionnaire, both subjective and objective,
and also assessed the relationship between total quality of life (TQOL)
and its individual subcomponents to social support. We also used
multivariate models to assess the possible role of age and other
variables as potential predictors of QOL and its subcomponents due to
their known correlation with satisfaction (Chand et al., 2004;
Blenkiron & Hammill, 2003; Clarkson & McCcCrone, 2000; and
Mercier et al., 1998).
Methodology
Study Population and Sampling
Convenience sampling was used to select subjects for the study.
Participants were recruited through personal appeal, and indirectly
through the residential manager at each facility. The study
participants resided at three separate residential facilities
Potential participants were informed of the nature of the study, the
survey method and the anticipated amount of time required for
participation. Patients were informed that their participation was
strictly voluntary and that there were no penalties for
non-participation. Any confidentiality concerns were also addressed.
Patients were also encouraged to discuss any concerns about the
objectives of the study.
Data collection
The modified Quality Of Life Questionnaire Interviewer Rating Version
questionnaire was administered to assess QOL. The
Multidimensional Scale of Perceived Social Support (MSPSS) was
administered to assess social support. Demographic and funding
information, as well as information on patients’ diagnosis was also
collected.
The QOL components assessed in the Bigelow questionnaire are: self and
home maintenance ability, financial situation, availability of
employment and transportation, available services, physical condition,
meaningful use of time, and ability to complete tasks. Acronyms used
for the nine subcomponents of QOL are listed in Table1.
Table 1. Acronyms used
for QOL and
its nine subcomponents
The MSPSS questionnaire is comprised of 12 items rated on a 7-point
Likert-type scale (response format ranges from, 1 = very strongly
disagree to 7 = very strongly agree). A higher score signifies
increased levels of perceived social support. The score on individual
items on the MSPSS were summed and divided by 12. Scores on the four
items that comprise each subscale were also summed and divided by 4
(Cecil, Stanley, Carrion, & Swann, 1995).
Canty-Mitchell & Zimet (2000) assessed the reliability and validity
of the MSPSS instrument. The Cronbach’s Alpha coefficient was .93; the
The Cronbach’s Alpha coefficient of the three subscales of family,
friends and significant other were .91, .89 and .91 respectively.
Correlation coefficients were used to assess the validity of the MSPSS
instrument by comparing it to the Adolescent Family Caring Scale
(AFCS). The results showed that for the family subscale the correlation
was .76, for the friends’ subscale it was .33, and for the significant
other subscale was .48 (Canty-Mitchell & Zimet, 2000).
In attempting to assess QOL of people with mental illness there is a
concern regarding the validity of self-reported ratings by patients.
Limitations on the validity of self-reported QOL may be partially
attributatble the psychopathology of the patients, which can distort
mental, emotional and social judgments (Atkinson, Zibin, & Chuang,
1997). Two safeguards were utilized to minimize any potential bias of
patient’s self-reported ratings. First, eleven questions from the
survey instruments were answered directly by the interviewer in order
to offset any response bias on the part of the patient. Secondly, the
questionnaire included both objective and subjective criteria .
This study was approved by the Touro University International
institutional review board.
Statistical analyses
All statistical analyses were performed using the SPSS Graduate Pack
13.0 for Windows program.
Total SS and support of friends, family and significant other, together
with age, gender, residence location, type of funding, marital status,
and length of stay were examined for their relationship to QOL and its
subcomponents via multiple regressions and MANCOVA.
Results
Data was collected on 83 psychiatric patients, 61 men and 18 women
(Table 2). The mean age of respondents was 38 years with a range of 20
to 57 years. The average length of stay at the residential facility was
55.5 months (4.6 years). Fifty-nine of the study participants were
Caucasian (71.1%), eight were Hispanic, seven were African American,
seven were Jewish American, and two were Asian. Sixty-seven patients
received Medicaid financial support and 16 received Medicare financial
support. Sixty-nine patients were single, nine were divorced and five
married. Among members of the study population, 38 patients had been
diagnosed with Schizophrenia or schizoaffective disorder, 22 patients
had bi-polar disorder, 18 had depression disorder and five patients
diagnosed with other psychiatric conditions (Table 2b).
Table 2a. Characteristics of
study participants (N=83) ____________________
Variables
N = 83 %
Gender
Male
65 78.3
Female
18 21.7
Ethnicity
Caucasian
59 71.1
Hispanic
8 9.6
African
American
7 8.4
Jewish
American
7 8.4
Asian
2 2.4
Marital status
Single
69 83.1
Divorced
9 6.0
Married
5 10.8
Residence location
LOCATION1
26 31.3
LOCATION2
23 27.7
LOCATION3
34 41.0
Funding
Medicaid
67 80.7
Medicare
16 19.3
_______________________________________________________________
Table 2b. Characteristics of
study participants (N=83) contd._________________
Variables
N = 83 %
Psychiatric conditions
Schizophrenia/schizoaffective
disorder
38 45.2
Bipolar
disorder
22 26.2
Depression
18 21.4
Other psychiatric conditions (Personality disorder,
ADD/ADHD, anxiety, panic, impulse control disorder
and obsessive compulsive
disorder)
5
6.0
________________________________________________________________
Study participants scored highest on QOLM and lowest on QOLE.
Participants tended to report low scores on QOLTR (Table 3).
Table 3. Descriptive
statistics – QOL and subcomponents (N = 83)
Variable Mean SD
# Questions Mean divided by
# questions asked
TQOL
159.9
15.6
56
2.9
QOLM
42.9
4.6
12
3.6
QOLE
14.1
7.5
9
1.6
QOLH
26.9
2.0
8
3.4
QOLSH
18.4
2.2
7
2.6
QOLU
18.8
3.4
6
3.1
QOLT
16.3
3.0
5
3.3
QOLPH 12.3
1.7
4
3.1
QOLF
7.0
0.9
3
2.3
QOLTR
3.3 1.6
2
1.7
QOLsub 55.45
7.58
17
3.3
QOLobj
106.0 9.67
39
2.7
Subjects reported having more social support from friends than from
family or from significant other. This is evidenced by the fact
that the mean scores on the ‘friends’ subcomponent of social support
were significantly higher than the mean scores of the ‘family’
and ‘significant other’ subcomponents (Table 4).
Table 4.
Descriptive statistics –
Social support and subcomponents (N =
83)
Variable
Mean SD #
Questions
Total social
support
69.6
14.7 12
Social support subcomponent
family
21.3
8.3 4
Social support subcomponent
friends
26.4
2.9 4
Social support subcomponent
significant other
21.9
7.4
4
Results of multiple
linear
regression using total social support as the main predictor and TQOL
and subcomponents
as dependent variables (N = 83)
<>
**p ≤ .01,*p ≤
.05, beta coefficients are reported
Funding (Medicaid
vs. Medicare), Gender (Men vs.
Women), Length of stay (months), Age
(years), Location 3 is used as a reference, Single status is
used as a
reference, total social support represents a score made up of family,
friends
and significant other. The coefficients
are the un-standardized coefficients.
Ten multiple regression procedures were performed on TQOL and
its subcomponents (QOLE, QOLF, QOLPH, QOLH, QOLSH, QOLM, QOLT, QOLU,
and QOLTR) with total social support as a main predictor of both TQOL
and its subcomponents (Table 5). Total social support was significantly
related to TQOL (B = .300, p ≤ .05). Other significant predictors of
TQOL were location 2 (B = 14.128, p ≤ .01) and length of stay (B =
.201, p ≤ .05). Significant predictors of QOLE included location 2 (B =
3.686, p ≤ .05), type of funding (B = 6.659, p ≤ .05), age (B = -.310,
p ≤ .01) and length of stay (B = .114, p ≤ .01). Total social support
was significantly related to QOLF (B = .017, p ≤ .05). Other
significant predictors of QOLF were location 1 (B = .664, p ≤ .01),
location 2 (B = .964, p ≤ .01), age (B = .040, p ≤ .05), and married
status (B = -.895, p ≤ .05). Using QOLPH as the dependent variable
divorced status was a significant negative predictor (B = –1.293, p ≤
.05). Using QOLH as the dependent variable length of stay was a
significant positive predictor (B = .028, p ≤ .05). Using QOLSH as the
dependent variable total social support was a significant positive
predictor (B = .040, p ≤ .05). Using QOLM as the dependent variable
residence location 2 was again a significant predictor (B = 2.987, p ≤
.01). Using QOLT as the dependent variable, type of funding was a
significant predictor (B = –2.795, p ≤ .05) with Medicaid patients
exhibiting greater QOLT than Medicare patients. Using QOLU as the
dependent variable significant predictors were location, with location
2 having significantly higher QOLU than location 3 (B = 3.552, p ≤
.01), age (B = .118, p ≤ .05), and marital status, married patients
having lower QOLU (B = –3.121, p ≤ .05). Using QOLTR as the dependent
variable, only length of stay was a significant predictor (B = .021, p
≤ .05). The R2 coefficients for predicting QOL and its subcomponents
were respectively TQOL – .304**, QOLE – .350**, QOLF – .327**, QOLPH
– .116, QOLH – .230*, QOLSH – .377**, QOLM – .359**, QOLT –
.356**, QOLU – .284, and QOLTR – .102 (**p ≤ .01, *p ≤ .05). A MANCOVA
analysis was also performed (data not shown). Thus, taking into account
all TQOL components as dependent variables at the same time, results
were consistent with the results of the linear regression analyses.
When objective QOL and subjective QOL were used as the dependent
variable respectively, a significant positive relationship emerged
between total social support and objective QOL (B = .176, p ≤ .05) and
between total social support and subjective QOL (B = .140, p ≤ .05).
Longer length of stay was associated with higher objective QOL (B =
.176, p ≤ .01), however, length of stay was not significantly related
to subjective QOL.
Linear regressions were also performed using the three subcomponents of
social support (family, friends, and significant other) as independent
variables of TQOL and its subcomponents. Social support from friends
was related to QOLH (B= .228, p ≤ .05) and tended towards positive
association with QOLF (B = .075, p= .075). Social support from family
tended to be associated with QOLSH but did not reach significance (B=
.062, p= .059). Social support from family was not significantly
related to other components of quality of life. Social support from a
significant other was associated with QOLM (B= .153, p ≤ .05).
Discussion
This study was focused on the relationship of social support and other
potential predictors to QOL and its subcomponents. The study sample
size was 83 people, made up mostly of single Caucasian males at three
separate residential facilities.
A significant association was revealed between social support and TQOL
in patients with mental illness at residential facilities. Furthermore,
the study showed positive associations between the different QOL
subcomponents, SQOL and OQOL areas, and total social support and its
three subcomponents. The results presented here reinforce previous
findings on the importance of social support to quality of life for
patients with mental illness (Mares et al, 2002; Goldberg et al, 2003;
Nelson el al, 1995). This study also showed a novel association between
total social support and the QOL subcomponents of QOLF and QOLSH.
Other novel features of the study were an examination of the
relationship between support from friends and QOLH, as well as an
exploration of the relationship between support from a significant
other and QOLM. The results presented here suggest that age, gender,
facility location, funding, length of stay and marital status may all
be significantly predictive of QOL in residential home clients.
As shown in table 3, residential home clients had high TQOL. Out of a
possible 224 points on the QOL questionnaire instrument, the patients’
mean score was 160 points (72% of the possible points), suggesting a
moderate to high self-reported level of QOL. The high QOL could be
attributed in part to the quality of mental health services and housing
that the patients received. Mental health services and housing were
found to be significant predictors of TQOL score.
Multivariate analyses of the data revealed that total social support
was related to QOLSH and QOLF. The increased levels of total social
support with regards to increased levels of self and home maintenance
and finance could indicate that patients put more effort in caring for
their personal living spaces and participating in the general care of
the residential facility and were more optimistic about their future
finances.
Social support from friends was significantly and positively related to
QOLF and was almost a significant predictor of QOLH. There was a
special significance for social support from friends for most of the
study participants. Almost all of the psychiatric patients reported
having some form of friendship with other psychiatric patients. Due in
part to the enduring nature of their mental illness, most patients did
not report having regular contact with their family members; moreover,
most did not maintain regular relationships with a significant other.
Of the subcomponents of Social Support, it would therefore be logical
to conclude from these results that social support from friends exerted
the strongest influence on overall social support in our sample of
residential home clients.
Social support from a significant other was only significantly and
positively related to QOLM. Social support from family only tended
towards a positive relationship with self and home maintenance QOLSH.
Age was not related to TQOL but was positively related to QOLF and
negatively related to QOLE. In addition the multivariate test revealed
that age was significantly related to QOLU.
In examining the role of gender, we found that female clients received
more social support from their families as well as higher QOLSH than
male clients (bivariate analyses of data not shown here).
However, it should be noted that only 21.7% of the study participants
were women, and all female clients were located at location 3. Females
may ascribe a higher level of importance to self and home maintenance
than do men, which could in principle account for the higher mean QOLSH
in female clients than in male clients. Female clients may also
have felt a greater stake in contributing to both their personal areas
and that of the facility, as compared to male clients.
Length of stay was significantly related to TQOL and QOLH. In addition
the multivariate analyses revealed that length of stay was
significantly related to QOLE, QOLH and QOLTR. These findings suggest
that psychiatric patients who stayed for longer periods of time at the
residential facilities were more likely to acclimate to their
surroundings, reporting increased levels of satisfaction with both
their housing and their quality of life. Patients who stayed for longer
periods of time at the residential homes were also more likely to seek
employment and transportation services, when compared to their
counterparts with shorter length of stay.
The type of patient funding, whether Medicare or Medicaid, was
influential upon QOLE and QOLT. Medicaid patients scored higher on QOLE
but lower on QOLT as compared to those on Medicare. Medicaid
funded 80.7% of the patients in our sample.
No significant relationship was found between marital status and TQOL.
However, when examining the subcomponents of QOL, divorced clients had
significantly lower QOLPH than single clients. Married clients
had significantly lower QOLF and QOLU as compared to single clients. It
should be noted that out of the 83 patients in the study, only five
patients were married and nine were divorced.
These findings about the role of marital status on quality of life were
somewhat unanticipated. Indeed, the results of previous
investigations (see for example, Chand et al., 2004; and Lang et
al., 2002) suggested a strong positive role of being married as a
predictor of overall life satisfaction (in addition to age and higher
income). The small number of married participants (5 married
patients) in the study could explain this discrepancy. Also, another
possible explanation for the lower score for both married and divorced
patients regarding the issue of finance, completing tasks and use of
time could be related to comparisons of their current activities, or
lack thereof, to their former lives.
Reported Quality of Life in subjects varied significantly from one
residential home to another. There was a relationship between
residence location and QOL with location 1 scoring higher on various
QOL components than location 3, while location 2 scored higher on QOLF
than location 3. There were notable differences between the three
locations with respect to both the gender of patients sampled, and the
total number of patients. For example, Location 3 was the only location
at which both men and women were housed, and it contained the largest
group size. Locations 1 and 2 were similar in design, and both
housed an all-male population. Here we speculate briefly as to the
reasons why clients at Locations 1 and 2 reported having higher quality
of life than clients at location 3. First, the larger number of
patients in the home at location 3 suggests that crowding may have some
role in reported quality of life; however, we did not measure this
factor directly. Secondly, the mixture of men and women at
Location 3 suggests that male/female interactions may not be
beneficial. Finally, Location 3 was located in a separate
geographic location from the other two homes that we sampled.
Thus, the geographic location itself may have been less favorable to
clients at Location 3.
The results of multivariate analyses demonstrate that total social
support was positively associated with both the objective and
subjective domains of QOL. Social support from friends was also
significantly related to both objective and subjective QOL. We found
that the lower level of reported quality of life in patients who lacked
social support was explainable, at least to some extent, by a low level
of connection to family members. Further, many of the patients with low
reported QOL were unable to sustain a relationship with a significant
other. The lack of connectedness to family and significant others
suggest that mental patients rely heavily instead upon social support
from friends, which affords them higher quality of life.
Previous research (see for example, Bussbach and Wiersma, 2002)
suggested that affective bias, poor insight, lack of adaptive processes
and persistently unfavorable life circumstances may all influence
subjective measurements of subjective quality of life. Further,
perceived QOL implies a subjective judgment about satisfaction that can
be affected by many variables. It would thus be reasonable to
expect a positive relationship between satisfaction with social support
and QOL (Caron, Tempier, Mercier, & Leouffre 1998). Previous
research by Tempier et al. 1998 suggested that subjective QOL in
patients with SMI tended to be lower for welfare recipients than for
patients with SMI who were not on welfare
Our findings on the impact of social support upon subjective QOL are
thus consistent with those of previous research (see for example, Lam
& Rosenheck, 2000). It is our hope that by carrying out our
study, the clients accrued some benefits. Indeed, focusing upon a
person’s subjective view of his or her QOL may be important in terms of
empowering that person, and in strengthening his or her involvement and
participation in the rehabilitative process (Lustig, Crowder, 2000).
Conclusions
Total SS was significantly related to total QOL. Of the nine
subcomponents of QOL, only two domains (self and home maintenance, and
financial services and concerns) were related to total social support.
SS from friends was significantly related to the QOL subcomponent of
housing, was close to significance as a positive predictor of the QOL
subcomponent of finance, and was also significantly related to both
objective and subjective QOL.
Perhaps the most significant finding reported here is that social
support from friends has a strong positive impact upon QOL in
residential home clients with SMI. For most of the patients,
social contact with friends was the most significant source of
interaction in their lives. The clients evidently relied more
heavily upon that connection than they did a family member or a
significant other as a source of social support. This highlighted
role of social support from friends is plainly evident upon examination
of the social network for many psychiatric patients in residential
homes- reduced connection to family members and an inability to sustain
a relationship with a significant other.
Study limitations
Here, we briefly discuss the limitations to our approach. First,
many of the items on the QOL questionnaire pertain to the type of
services received and satisfaction with the services received by the
residential psychiatric patients. Thus, some of these items
cannot be largely affected by social support from friends, family or a
significant other. In the multivariate analyses the R2 value was 0.3,
or 30% of the variance. In other words, the model did not explain about
70% of the concerns regarding QOL. Areas for further exploration
of these influential factors to QOL include measurement of patients’
emotions and feelings regarding their specific living situation, and an
assessment of the impact of different therapeutic approaches upon
mental health treatments. Additionally, factors external to the
current lives of patients at the residential facility are perhaps
worthy of further exploration for their impact upon QOL.
Second, the instrument that we used to measure QOL did not fully
completely assess transportation, finance, or the physical health of
the patient. Patients have varied needs, some requiring transportation
and financial services while other patients do not; these issues were
explored only superficially in our study. We also did not directly
measure the direct impact of variations in psychiatric medications
prescribed to the patients, type of care received for those with
chronic illness, nor the overall impact of chronic illness upon daily
life.
Thirdly, some of the personal information that we gathered on patients
was not independently verifiable, and could have been influenced by
bias. In order to ensure patient confidentiality, we did not seek
access to medical records or other documentation required to verify
patients’ responses to questionnaire items. Lastly, non-normal
distribution of the QOL subcomponents and residuals may have affected
the study results.
The results confirm the importance of social support to Quality of Life
in patients with mental illness at residential home facilities.
The findings also suggest a prominent role of marital status, finance,
self and home maintenance, and support from friends in this
relationship of social support to quality of life.
